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What is Big Data?


Big data is nothing but a collection of huge amount of data that grows exponentially with time. It includes large amount of data that is complex and cannot be stored or processed using traditional management tools.

Let us understand big data with the help of few examples.

a) The New York Stock exchange generates approximately 1TB data every day. b) A survey reveals that about 500TB new data gets consumed on Facebook in the form of photos, videos, messages, comments, etc. c) A single Jet engine generates around 10TB of data in 30 minutes of its flight time. With thousands of flights plying about, the data generated can reach to several Petabytes.


Big data can be divided into 3 broad categories;

1. Structured
Data that can be accessed, processed and stored in a fixed format is known as structured data. The computer techniques have developed to a great extent and the format to work with a particular type of data is known in advance now. However, this does not help in cases where the data keeps growing to an extent that it touches multiple range of Zettabyte. That is where the term ‘big data’ originates. It can be challenging to process and store such large amount of data.


2. Unstructured
Data that is huge and has no proper structure to it is defined as unstructured data. This sort of data poses several challenges in terms of processing and obtaining a value of it. For instance, a heterogeneous data comprising of images, videos, text files etc can be considered as unstructured data. Several organizations have a huge amount of data but unfortunately are not aware of how to derive value out of it as most of the data is in unstructured format. A best example to explain unstructured data is output by Google search.

3. Semi-Structured
This can be a combination of both structured as well as unstructured data. You can mistake the data to be in a structured format even though it may not be defined thoroughly. A data in XML file is a good example of semi-structured data.

What are the Characteristics of Big Data?

1. Size or Volume
From the name itself one can have a fair idea about the size of the data being huge. The size of any data is crucial as it helps determine a value out of that data. Also, must understand that just any data cannot be referred to as Big Data. The volume of the data is important in determining whether it can be referred to as Big Data or not. Hence, it can be safely said that the ‘volume’ of the data is an important characteristic that helps in determining if a data can be referred to as Big Data.


2. Variety
By variety, we mean both structured and unstructured data. Here, the data can be from several different sources. Earlier, most of the applications used data in the form of either spreadsheets or databases. Today, however, the scenario has changed and data can be of any form; videos, PDFs, audios, photos, monitoring devices and much more. Variety of data brings with uncertainty in terms of mining, analyzing and storing of data.


3. Velocity
This refers to the speed at which data is generated. The speed at which the data is generated and processed to meet the demand is what determines its real potential.

Velocity refers to the speed at which the data flows from various sources such as application logs, networks, business processes, social media sites, mobile devices, sensors, etc. The flow of data is continuous and huge in volume.

4. Variability
Sometimes data can be really inconsistent or variable. This hampers the process of handling data and managing it effectively.

Benefits of Big Data

If you are able to process Big Data efficiently then it can offer you several benefits.
• Allows Businesses to Utilize Outside Intelligence and take Better Decisions Businesses will be able to achieve their goals faster by accessing data from search engines and social media sites.

• Provide Better Customer Service
Big Data technologies have replaced the traditional methods of customer feedback. These new systems natural language processing along with Big data technologies are made use to evaluate and read customer responses.

• Better Operational Efficiency
'Big Data' technologies can be utilized as a landing zone for new data. After this the data can be moved to a data warehouse. This process can also help organizations to take care of data is not used frequently.

• Big data technology helps organizations to identify any risk to product or service at an early stage

Read the full article on: http://www.satejinfotech.in/
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